Learn MIT 6.S094- Deep Learning and Self-Driving Cars Course!
Course website: https://selfdrivingcars.mit.edu/ ,all slides are videos can be downloaded from this page
There are 5 lectures, each about 90 minutes.
Lecture 2: Deep reinforcement learning
learning summary deadline 20171206
Material to research:
1. CASE study
2. MIT lecture 2: see https://selfdrivingcars.mit.edu/
3.Reference:
Please cover all the related items in the case study material that you can find in lesson 2.You need to do extensive research.
Submit your summary of lesson 2 in the form of PPT, try to use multimedia presentation:
list the related key term or item in outline of your PPT and elaborate each one with sufficient materials and summarize it.
submit your own deep traffic code:
Stage 1: study MIT course
Learn MIT 6.S094- Deep Learning and Self-Driving Cars Course!Course website: https://selfdrivingcars.mit.edu/ ,all slides are videos can be downloaded from this page
There are 5 lectures, each about 90 minutes.
Lecture 2: Deep reinforcement learning
learning summary deadline 20171206
Material to research:
1. CASE study
2. MIT lecture 2: see https://selfdrivingcars.mit.edu/
3.Reference:
- http://www.algorithmdog.com/series/rl-series 强化学习系列文章
- https://selfdrivingcars.mit.edu/resources/ course resources -- see Deep Reinforcement Learning
- http://karpathy.github.io/2016/05/31/rl/ Deep Reinforcement Learning: Pong from Pixels
- https://www.intelnervana.com/demystifying-deep-reinforcement-learning/ 解密强化学习
- https://deepmind.com/blog/deep-reinforcement-learning/
- http://cs.stanford.edu/people/karpathy/convnetjs/ ConvNetJS
- http://cs.stanford.edu/people/karpathy/convnetjs/demo/rldemo.html ConvNetJS Deep Q Learning Demo
- https://github.com/karpathy/convnetjs/blob/master/build/deepqlearn.js
- http://cs.stanford.edu/people/karpathy/convnetjs/docs.html last section
- https://arxiv.org/pdf/1312.5602v1.pdf Playing Atari with Deep Reinforcement Learning
- https://github.com/parilo/DeepTraffic-solution 75.28mph solution on deep traffic for your reference!
work on your deep traffic project:tutorial: https://selfdrivingcars.mit.edu/deeptraffic/
simulation: https://selfdrivingcars.mit.edu/deeptrafficjs/
Please cover all the related items in the case study material that you can find in lesson 2.You need to do extensive research.
Submit your summary of lesson 2 in the form of PPT, try to use multimedia presentation:
list the related key term or item in outline of your PPT and elaborate each one with sufficient materials and summarize it.
submit your own deep traffic code:
Submission:
HL students
(SL Optional)